Given the importance of hyperelastic constitutive models in the design of engineering components, researchers have been developing the improved and new constitutive models in search of a more accurate and even universal performance. Here, a modified hyperelastic constitutive model based on the Yeoh model is proposed to improve its prediction performance for multiaxial deformation of hyperelastic polymeric materials while retaining the advantages of the original Yeoh model. The modified constitutive model has one more correction term than the original model. The specific form of the correction term is a composite function based on a power function represented by the principal stretches, which is derived from the corresponding residual strain energy when the Yeoh model predicts the equibiaxial mode of deformation. In addition, a parameter identification method based on the cyclic genetic-pattern search algorithm is introduced to accurately obtain the parameters of the constitutive model. By applying the modified model to the experimental datasets of various rubber or rubber-like materials (including natural unfilled or filled rubber, silicone rubber, extremely soft hydrogel and human brain cortex tissue), it is confirmed that the modified model not only possesses a significantly improved ability to predict multiaxial deformation, but also has a wider range of material applicability. Meanwhile, the advantages of the modified model over most existing models in the literatures are also demonstrated. For example, when characterizing human brain tissue, which is difficult for most existing models in the literature, the modified model has comparable predictive accuracy with the third-order Ogden model, while maintaining convexity in the corresponding deformation domain. Moreover, the effective prediction ability of the modified model for untested equi-biaxial deformation of different materials has also been confirmed using only the data of uniaxial tension and pure shear from various datasets. The effective prediction for the untested equibiaxial deformation makes it more suitable for the practice situation where the equibiaxial deformation of certain polymeric materials is unavailable. Finally, compared with other parameter identification methods, the introduced parameter identification method significantly improves the predicted accuracy of the constitutive models; meanwhile, the uniform convergence of introduced parameter identification method is also better.

The adhesive performance of biomimetic controllable adhesive based on wedge-shaped microstructures is affected by some relevant control parameters in the process of loading and unloading. An appropriate selection of these control parameters is of great significance for its effective application. However, few researches have concentrative and comprehensive explored these control parameters. In order to make up for the shortcoming, this study systematically explored the macroscopic adhesive performance of the self-developed wedge-shaped microstructures under different loading and unloading control parameters. The results show that preloading depth and tangential dragging distance have a positive effect on the adhesive performance, while preloading angle and peeling angle have a negative effect on the adhesive performance. Specifically, a low preloading angle can weaken the normal preloading force under same preloading depth, thereby improving the preloading benefit; the application of tangential dragging distance can also induce the normal preloading force generated in the preloading stage to change to the adhesion, so as to stimulate more adhesion. Based on the interactive analysis of these control parameters, it can be sure that applying a moderate normal preloading force and a larger tangential dragging distance to the wedge-shaped microstructures at low preloading angle not only can make the wedge-shaped microstructures possess better adhesive capacity, but also can obtain a good preloading benefit. In addition, the promotion effect of a low peeling angle on the adhesive performance also implies that a higher peeling angle should be used to realize the easy detachment of the adhesive interface. The first concentrative and comprehensive investigation of the relevant control parameters of wedge-shaped microstructures lays the foundation for designing climbing robot or adhesive gripper based on the wedge-shaped microstructures, and also provides guidance for formulating the corresponding control strategies.